mirror of
https://github.com/pybind/pybind11.git
synced 2024-11-22 21:25:13 +00:00
b0292c1df3
This extends the trivial handling to support trivial handling for Fortran-order arrays (i.e. column major): if inputs aren't all C-contiguous, but *are* all F-contiguous, the resulting array will be F-contiguous and we can do trivial processing. For anything else (e.g. C-contiguous, or inputs requiring non-trivial processing), the result is in (numpy-default) C-contiguous layout.
59 lines
2.4 KiB
C++
59 lines
2.4 KiB
C++
/*
|
|
tests/test_numpy_vectorize.cpp -- auto-vectorize functions over NumPy array
|
|
arguments
|
|
|
|
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
|
|
|
|
All rights reserved. Use of this source code is governed by a
|
|
BSD-style license that can be found in the LICENSE file.
|
|
*/
|
|
|
|
#include "pybind11_tests.h"
|
|
#include <pybind11/numpy.h>
|
|
|
|
double my_func(int x, float y, double z) {
|
|
py::print("my_func(x:int={}, y:float={:.0f}, z:float={:.0f})"_s.format(x, y, z));
|
|
return (float) x*y*z;
|
|
}
|
|
|
|
std::complex<double> my_func3(std::complex<double> c) {
|
|
return c * std::complex<double>(2.f);
|
|
}
|
|
|
|
test_initializer numpy_vectorize([](py::module &m) {
|
|
// Vectorize all arguments of a function (though non-vector arguments are also allowed)
|
|
m.def("vectorized_func", py::vectorize(my_func));
|
|
|
|
// Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the vectorization)
|
|
m.def("vectorized_func2",
|
|
[](py::array_t<int> x, py::array_t<float> y, float z) {
|
|
return py::vectorize([z](int x, float y) { return my_func(x, y, z); })(x, y);
|
|
}
|
|
);
|
|
|
|
// Vectorize a complex-valued function
|
|
m.def("vectorized_func3", py::vectorize(my_func3));
|
|
|
|
/// Numpy function which only accepts specific data types
|
|
m.def("selective_func", [](py::array_t<int, py::array::c_style>) { return "Int branch taken."; });
|
|
m.def("selective_func", [](py::array_t<float, py::array::c_style>) { return "Float branch taken."; });
|
|
m.def("selective_func", [](py::array_t<std::complex<float>, py::array::c_style>) { return "Complex float branch taken."; });
|
|
|
|
|
|
// Internal optimization test for whether the input is trivially broadcastable:
|
|
py::enum_<py::detail::broadcast_trivial>(m, "trivial")
|
|
.value("f_trivial", py::detail::broadcast_trivial::f_trivial)
|
|
.value("c_trivial", py::detail::broadcast_trivial::c_trivial)
|
|
.value("non_trivial", py::detail::broadcast_trivial::non_trivial);
|
|
m.def("vectorized_is_trivial", [](
|
|
py::array_t<int, py::array::forcecast> arg1,
|
|
py::array_t<float, py::array::forcecast> arg2,
|
|
py::array_t<double, py::array::forcecast> arg3
|
|
) {
|
|
size_t ndim;
|
|
std::vector<size_t> shape;
|
|
std::array<py::buffer_info, 3> buffers {{ arg1.request(), arg2.request(), arg3.request() }};
|
|
return py::detail::broadcast(buffers, ndim, shape);
|
|
});
|
|
});
|